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A network approach for identifying and delimiting biogeographical regions

Author

Listed:
  • Daril A. Vilhena

    (University of Washington)

  • Alexandre Antonelli

    (University of Gothenburg
    Gothenburg Botanical Garden, Carl Skottsbergs gata 22B)

Abstract

Biogeographical regions (geographically distinct assemblages of species and communities) constitute a cornerstone for ecology, biogeography, evolution and conservation biology. Species turnover measures are often used to quantify spatial biodiversity patterns, but algorithms based on similarity can be sensitive to common sampling biases in species distribution data. Here we apply a community detection approach from network theory that incorporates complex, higher-order presence–absence patterns. We demonstrate the performance of the method by applying it to all amphibian species in the world (c. 6,100 species), all vascular plant species of the USA (c. 17,600) and a hypothetical data set containing a zone of biotic transition. In comparison with current methods, our approach tackles the challenges posed by transition zones and succeeds in retrieving a larger number of commonly recognized biogeographical regions. This method can be applied to generate objective, data-derived identification and delimitation of the world's biogeographical regions.

Suggested Citation

  • Daril A. Vilhena & Alexandre Antonelli, 2015. "A network approach for identifying and delimiting biogeographical regions," Nature Communications, Nature, vol. 6(1), pages 1-9, November.
    • Handle: RePEc:nat:natcom:v:6:y:2015:i:1:d:10.1038_ncomms7848
    DOI: 10.1038/ncomms7848
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    Cited by:

    1. Rebecca B. Cooper & Joseph T. Flannery-Sutherland & Daniele Silvestro, 2024. "DeepDive: estimating global biodiversity patterns through time using deep learning," Nature Communications, Nature, vol. 15(1), pages 1-14, December.
    2. Cassiano A F R Gatto & Mario Cohn-Haft, 2021. "Spatial Congruence Analysis (SCAN): A method for detecting biogeographical patterns based on species range congruences," PLOS ONE, Public Library of Science, vol. 16(5), pages 1-19, May.
    3. Daniel J McGarvey & Joseph A Veech, 2018. "Modular structure in fish co-occurrence networks: A comparison across spatial scales and grouping methodologies," PLOS ONE, Public Library of Science, vol. 13(12), pages 1-20, December.
    4. Runxi Wang & Jamie M. Kass & Chhaya Chaudhary & Evan P. Economo & Benoit Guénard, 2024. "Global biogeographic regions for ants have complex relationships with those for plants and tetrapods," Nature Communications, Nature, vol. 15(1), pages 1-11, December.
    5. Miho Kamei & Alessio Mastrucci & Bas J. van Ruijven, 2021. "A Future Outlook of Narratives for the Built Environment in Japan," Sustainability, MDPI, vol. 13(4), pages 1-20, February.

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